Defense Notices

Active is a Haskell library for creating animations driven by time. The key concept is that every animation has its own starting and ending time and the motion of each element can be defined as a function of time. This underlying idea is intuitive and simple enough for the users to understand that it has created a space for simple animations, called “Functional Active programming”. Although there are many FRP libraries available, FRP libraries are often challenging to use for simple animations. 
In this project, we have added some reactive features to the Active library as an attempt to enhance the active programming space without complicating the underlying principles. This will let Active elements to detect collisions, or a mouse click event, and change their behavior accordingly. Having built-in reactive features equips the Active programmers with extra tools at their disposal and significantly reduces the efforts needed to code such reactions. These reactive features have been implemented on top of the Blank Canvas. 

Efficient use of the vast spectrum offered by fiber-optic links by an end user with relatively small bandwidth requirement is possible by partitioning a high speed signal in a wavelength channel into multiple low-rate subcarriers. Multi-carrier systems not only ensure optimized use of optical and electrical components, but also tolerate transmission impairments. The purpose of this research is to theoretically and experimentally study mixing among subcarriers in Radio-Over-Fiber (RoF) and direct detections systems. 
For an OFDM-RoF system, we present a novel technique that minimizes the RF domain signal-signal beat interference, relaxes the phase noise requirement on the RF carrier, realizes the full potential of the optical heterodyne technique, and increases the performance-to-cost ratio of RoF systems. We demonstrate a RoF network that shares the same RF carrier for both downlink and uplink, avoiding the need of an additional RF oscillator in the customer unit. 
For direct detection systems, we propose theoretical and experimental investigation of impact of semiconductor optical amplifier nonlinearities on Compatible-SSB signals. As preliminary work, we present experimental comparison of performance degradation of coherent optical OFDM and single carrier Nyquist pulse modulated systems in a nonlinear environment. Furthermore, analysis of distribution properties of optical phases driving a dual-drive MZM and their dependence on scaling factor are proposed for Compatible-SSB modulation format through simulations and experimental results. An optimum scaling factor needs to be found that minimizes residual sideband and signal-signal beat interference in such systems. 

The WFG2013 project uses Analog Devices AD9915 DDS ICs at up to 2.5 GS/s as basic building blocks for a scalable,synchronous, multichannel DDS system. Four DDS ICs are installed on a daughterboard with an Altera Cyclone 5E FPGA as a controller. The daughterboard can run standalone (Solo), in conjunction with another daughterboard (Duo), or N daughterboards surfing a motherboard (Mucho). 

Synchronization between configured DDS ICs is achieved via the on-chip SYNC-IN and SYNC-OUT signals. The master DDS (only one per configuration) generates the SYNC_OUT signal, which is distributed to the SYNC_IN pins on all DDS ICs, including the master. The synchronization signal distribution network was designed to minimize skew such that the SYNC_IN signal reaches the all DDSs at virtually the same time. Even if some skew appears, the AD9915's SYNC_IN and SYNC_OUT signals have adjustable delay. The SYNC_IN signal causes the DDSs to assume a known state. Because all of the DDSs reach the same state at the same time, they are, by definition synchronized.

Websockets is a protocol that provides a full-duplex communication channel over a single TCP connection between a web server and web client. Kansas-comet is long polling solution that allows web servers written in the functional programming language Haskell to push data to browser clients. Implementing kansas-comet with websockets enables pushing data from web servers to clients with reduced data loads and network latency, which helps in scaling web applications. Other applications, like the graphics library blank canvas, use kansas-comet, so improving kansas-comet also improves these applications as well. 

In this project, we add websockets to kansas-comet for the sake of improving client-server communications by providing a modern full duplex communication channel. Modern web browsers support the websocket protocol but it is important for kansas-comet to also provide backward compatibility. So, the new kansas-comet now implements a mechanism that falls back to long polling strategy when browser does not support websocket or when applications using kansas comet does not implement websockets. We use JavaScript and the kansas-comet JavaScript library on client browsers, and we use websocket, wai-websockets and warp libraries on the server side to implement websockets in kansas comet.

Increasing focus on global warming has challenged the scientific community to develop ways to mitigate its adverse effects. This is more so important as different technologies become an integral part of daily human life. Mobile wireless networks and mobile devices form a significant part of these technologies. It is estimated that there are over four billion mobile phone subscribers worldwide and this number is still growing as more people get connected in developing countries. In addition to the growing number of subscribers, there is an explosive growth in high data applications among mobile terminal users. This has put increased demand on the mobile network in terms of energy needed to support both the growth in subscribers and higher data rates. The mobile wireless industry therefore has a significant part to play in the mitigation of global warming effects. To achieve this goal, there is a need to develop and design energy efficient communication schemes for deployment in future networks and upgrades to existing networks. This is not only done in the wireless communication infrastructure but also in mobile terminals. In this project a practical power consumption model which includes circuit power consumption from the different components in a transceiver chain is analyzed. This is of great significance to practical system design when doing energy consumption and energy efficiency analysis. The proposed power consumption model is then used to evaluate the energy efficiency in the context of cooperative Multiple Input Multiple Output(MIMO)systems.

The reliance of Unmanned Aerial Vehicles (UAVs) on Global Navigation Satellite System (GNSS) for autonomous operation represents a significant vulnerability to their reliable and secure operation due to signal interference, both incidental (e.g. terrain shadowing, ionospheric scintillation) and malicious (e.g. jamming, spoofing). An accurate and reliable alternative UAV navigation system is proposed that exploits Signals of Opportunity (SOP) thus offering superior signal strength and spatial diversity compared to satellite signals. Given prior knowledge of the transmitter's position and signal characteristics, the proposed technique utilizes triangulation to estimate the receiver's position. Dual antenna interferometry provides the received signals' Angle of Arrival (AoA) required for triangulation. Reliance on precise knowledge of the antenna system's orientation is removed by combining AoAs from different transmitters to obtain a differential Angles of Arrival (dAoAs). Analysis, simulation, and experimental techniques are used to characterize system performance; a path to miniaturized system integration is also presented.

Batteries are used everywhere and with the rise of the portable devices it is crucial to lower the power dissipation and to improve the battery runtime. An efficient way to describe the electrical behavior of a battery helps the designer to better predict and optimize the battery runtime and circuit performance. In this project a suggested electrical circuit model is used to evaluate the battery characteristics of an alkaline cell and a rechargeable NiMH cell and the same is implemented in Cadence environment. The measured data is compared with the simulated data and the results are discussed further. This circuit model is efficient in modeling the behavior of the batteries used in this project and can be extended to various other types of batteries.

This paper proposes a novel extension to the Attribute Blocks visualization technique that can be applied to visualizations containing many attributes. The Attribute Blocks visualization scheme is a technique that divides the visualization space into a regular pattern of small cells where each cell displays only one attribute. This paper recommends that the goal of a pattern design should be to have each attribute share equal length edges with each other attribute. This goal imposes new constraints on the number of attributes that can be simultaneously displayed, hence one significant challenge was to develop a new strategy that would allow more flexible pattern geometry and evaluating the effectiveness of this strategy with real data sets.

A face detection and recognition system is a biometric identification mechanism which compared to other methods such as finger print identification, speech, signature, hand written and iris recognition is shown to be more important both theoretically and practically. In principle, the biometric identification methods use a wide range of techniques such as machine learning, machine vision, image processing, pattern recognition and neural networks. The methods have various applications such as in photo and film processing, control access networks, etc. In recent years, the automatic recognition of a human face has become an important problem in pattern recognition. The main reasons are that structural similarity of human faces and great impact of illumination conditions, facial expression and face orientation. Face recognition is considered one of the most challenging problems in pattern recognition. A face recognition system consists of two main components, face detection and recognition. In this dissertation we will design and implement a detection and recognition face system using color images with multiple faces. In color images, the information of skin color is used in order to distinguish between the skin pixels and non-skin pixels, dividing the image into some components. The next step is to decide which of these components belong to human face. After face detection, the faces which were detected in the previous step are to be recognized. Appearance based methods used in this work are one of the most important methods in face recognition due to the robustness of the algorithms to head rotation in the images, noise, low quality images, and other challenges.

This work formally introduces a generalized fuzzy logic and interval clustering (FLIC) technique which,when integrated with existing supervised learning algorithms, improves their performance. FLIC is a method that was first integrated with neural network in order to improve neural network’s performance in drug discovery using high throughput screening (HTS). This research strictly focuses on binary classification problems and generalizes the FLIC in order to incorporate it with other machine learning algorithms. In most binary classification problems, the class boundary is not linear. This pose a major problem when the number of outliers are significantly high, degrading the performance of the supervised learning function. FLIC identifies these misclassifications before the training set is introduced to the learning algorithm. This allows the supervised learning algorithm to learn more efficiently since it is now aware of those misclassifications. Although the proposed method performs well with most binary classification problems, it does significantly well for data set with high class asymmetry. The proposed method has been tested on four well known data sets of which three are from UCI Machine Learning repository and one from BigML. Tests have been conducted with three well known supervised learning techniques: Decision Tree, Logistic Regression and Naive Bayes. The results from the experiments show significant improvement in performance. The paper begins with a formal introduction to the core idea this research is based upon. It then discusses a list of other methods that have either inspired this research or have been referred to, in order to formalize the techniques. Subsequent sections discuss the methodology and the algorithm which is followed by results and conclusion. 

Keyword: supervised learning, binary classification, fuzzy logic, clustering